1. Field of the Invention
The present invention relates to a machine learning apparatus and method for learning an arrangement position of a magnet in a motor rotor, and a rotor design apparatus including the machine learning apparatus.
2. Description of the Related Art
FIG. 11 is a schematic view explaining assemblage a rotor of a general synchronous motor. For example, as described in Japanese Laid-open Patent Publication No. 2010-233325, a rotor 100 of a synchronous motor is formed such that a plurality of magnets 102 are arranged on a circumferential surface of a core 101.
Since each of the magnets arranged on the core forming the rotor has a variation in magnetic flux density, cogging torque varies depending on how the magnets are arranged on the core (arrangement position). In other words, the smoothness of feed of the rotor assembled (cogging torque) may sometimes deteriorate depending on the arrangement positions of the magnets.
Conventionally, there is a method for optimizing the smoothness of feed by adding a component for adjusting the magnetic flux density of each individual magnet when a variation in the magnetic flux density of each individual magnet is taken into account during assembly of a rotor, as in Japanese Laid-open Patent Publication No. 2010-233325. However, there is a problem in that due to the addition of the component, the cost is increased, and time is required for adjustment.
Further, the relationship between cogging torque (smoothness of feed) and arrangement positions of magnets can be simulated by commercially available analysis software. However, for example, when n pieces of magnets (where n is a natural number) are arranged on a core, there are “n!” (i.e., factorial of n) orders of arrangement of the magnets. It is unrealistic and virtually difficult to measure the magnetic flux density of each of n pieces of magnets and then perform a simulation analysis of the magnitude of cogging torque for all “n!” arrangement patterns of the magnets, thereby determining the arrangement positions of the magnets for which the magnitude of cogging torque is minimized (the smoothness of feed of the rotor is optimized).